Selected article for: "residual time series and return rate"
Author: Taranjot Kaur; Sukanta Sarkar; Sourangsu Chowdhury; Sudipta Kumar Sinha; Mohit Kumar Jolly; Partha Sharathi Dutta
Title: Anticipating the novel coronavirus disease (COVID-19) pandemic
  • Document date: 2020_4_10
    • ID: 1xenvfcd_17
    Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.08.20057430 doi: medRxiv preprint FIG. 4. The probability distribution of Kendall-Ï„ test statistic on a set of 1000 surrogate time-series generated by bootstrapping residual time-series of the original data. Histograms depict the distribution of the test statistic for the surrogate time-series return rate (left panels) and autocorrelatio.....
    Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.08.20057430 doi: medRxiv preprint FIG. 4. The probability distribution of Kendall-Ï„ test statistic on a set of 1000 surrogate time-series generated by bootstrapping residual time-series of the original data. Histograms depict the distribution of the test statistic for the surrogate time-series return rate (left panels) and autocorrelation function at lag-1 (right panels). Solid lines indicate the limit beyond which the Kendall-Ï„ of the surrogate data is higher (lower) than the statistic observed in the ACF(1) (return rate) of the original time-series.

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